Multi‐modal deep learning for joint prediction of otitis media and diagnostic difficulty

Multi‐modal deep learning for joint prediction of otitis media and diagnostic difficulty

Abstract Objectives In this study, we propose a diagnostic model for automatic detection of otitis media based on combined input of otoscopy images and wideband tympanometry measurements. Methods We present a neural network‐based model for the joint prediction of otitis media and diagnostic difficul...

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Bibliographic Details
Main Authors: Josefine Vilsbøll Sundgaard, Morten Rieger Hannemose, Søren Laugesen, Peter Bray, James Harte, Yosuke Kamide, Chiemi Tanaka, Rasmus R. Paulsen, Anders Nymark Christensen
Format: Article
Language:English
Published: Wiley 2024-02-01
Series:Laryngoscope Investigative Otolaryngology
Subjects:
computer‐aided diagnosis
deep learning
diagnostic difficulty
otitis media
Online Access:https://doi.org/10.1002/lio2.1199

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